Sökning: "Federerad Inlärning"

Visar resultat 6 - 10 av 13 uppsatser innehållade orden Federerad Inlärning.

1. 6. Cluster selection for Clustered Federated Learning using Min-wise Independent Permutations and Word Embeddings

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Pulasthi Raveen Bandara Harasgama; [2022]
   Nyckelord :Federated learning; Distributed machine learning; Clustering; Word Embeddings; Federerad inlärning; Distribuerad maskininlärning; Klustring; Ordinbäddningar;

   Sammanfattning : Federated learning is a widely established modern machine learning methodology where training is done directly on the client device with local client data and the local training results are shared to compute a global model. Federated learning emerged as a result of data ownership and the privacy concerns of traditional machine learning methodologies where data is collected and trained at a central location. LÄS MER

3. 7. Federated Learning for Market Surveillance

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Philip Song; [2022]
   Nyckelord :Federated Learning; Machine Learning; Market Surveillance; Anomaly Detection; LSTMAutoencoder; Federated Learning; Maskininlärning; Marknadsövervakning; Anomaliupptäckande; LSTMAutoencoder;

   Sammanfattning : The increasing complexity of trading strategies, when combined with machine learning models, forces market surveillance corporations to develop increasingly sophisticated methods for recognizing potential misuse. One strategy is to employ traders’ weapons against themselves, namely machine learning. LÄS MER

4. 8. Decentralized Large-Scale Natural Language Processing Using Gossip Learning

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Abdul Aziz Alkathiri; [2020]
   Nyckelord :gossip learning; decentralized machine learning; distributed machine learning; NLP; Word2Vec; data privacy; skvallerinlärning; decentraliserad maskininlärning; distribuerad maskininlärning; naturlig språkbehandling; Word2Vec; dataintegritet;

   Sammanfattning : The field of Natural Language Processing in machine learning has seen rising popularity and use in recent years. The nature of Natural Language Processing, which deals with natural human language and computers, has led to the research and development of many algorithms that produce word embeddings. LÄS MER

5. 9. Time to Next Flow Classification in Mobile Networks with Federated Learning

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Alex Knight-Williams; [2020]
   Nyckelord :;

   Sammanfattning : Understanding traffic dynamics and user demand in a cellular network is essential for effective resource management, which in turn improves the network’s energy and cost efficiency. This thesis focuses on the task of classifying the time until the arrival of the next flow at a user level in a real network traffic data set. LÄS MER

7. 10. Dynamic GAN-based Clustering in Federated Learning

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Yeongwoo Kim; [2020]
   Nyckelord :Clustering; Federated Learning; Time Series Forecasting; ClusterGAN; Hypothesis- based Clustering; Kluster; Federerad inlärning; Prognoser för tidsserier; ClusterGAN; hypotesbaserat kluster;

   Sammanfattning : As the era of Industry 4.0 arises, the number of devices that are connectedto a network has increased. The devices continuously generate data that hasvarious information from power consumption to the configuration of thedevices. LÄS MER